Communication Pattern

Communication patterns, encompassing how information flows and influences interactions among agents (individuals, robots, or even software entities), are a central focus of current research across diverse fields. Studies explore how these patterns emerge and evolve in various contexts, employing models ranging from graph neural networks analyzing continuous dynamic systems to agent-based models simulating opinion formation and social balance in networks. Understanding these patterns is crucial for improving human-robot collaboration, optimizing influence in social networks, and developing more accurate predictions in complex systems like disease spread. This research contributes to a deeper understanding of information dynamics and their impact on collective behavior.